Nowadays most of the people are going out to grab food, the majority of individuals relying on food applications. Though Zomato is popular food app in India, it deals with few challenges like – extreme market competition, loss of market shares, negative impact on brand etc. It experiences a major drop of orders during the month of October, which is a festival season that leads to drop down of revenue. Zomato came up with a solution for this problem, during festival season Zomato provides discounts and coupons on food that they purchase and asked restaurants and food stalls to keep open so that customers can make order even on festival season. The few root cause for Zomato are delivery issues and delay deliveries that can leads to unhappy customers and opt other food apps, more competition from other food apps which provides festival offers and discounts can make the customers to switch other food apps, customers doesn’t come forward to purchase when they look high cost on food menu without discounts, and during festival time people more likely to eat outside rather than to order food from food apps. To increase more and more deliveries Zomato should ensure with good quality of food, providing transparency in order- tracking and delivery of meals in time efficiently, and finally to resolve competition over other apps Zomato needs to provide personalized services and make sure the deliveries speed and accurate. Zomato make use of machine learning to predict real time challenges such as allocating delivery partners, estimating time for preparation of food and food delivery, and removing or deducting fake customer reviews. It also uses ML to digitalize the food menu and identifies the items included in that. It includes Natural Language Processing (NLP) to extract the structured data from unstructured data from food menu. Keywords:- Importing and Cleaning Data, Statistical Methods, Visualization Techniques, Carrying Out Statistical Tests, Model Prediction.